Computational Algorithmization: Limitations in Problem Solving Skills in Computational Sciences Majors at University of Oriente

Article excerpt

(ProQuest: ... denotes formulae omitted.)

INTRODUCTION

The process of computerization of society has gained a great boom in recent times by encouraging the application of Information and Communication Technologies (ICT) to different spheres and sectors of society, in order to achieve greater efficiency through the optimization of resources and the increase of productivity in these areas (Salgado, Alonso & Gorina 2014). For developing countries, such as Cuba, this purpose is a challenge that has led them to identify the need to introduce ICT into the social practice and to achieve an informatic culture that facilitates sustainable development. However, to carry out this purpose requires competent professionals, capable of acquiring that culture and developing it from the ways of acting in their profession (Fergusson et al. 2015).

This requirement has resulted in Cuba have included computer courses in the curriculum of numerous university major, such as bachelor degrees in Mathematics, Physics, Biology, among others, and Mechanical, Biomedical and Electrical engineering. They have also created careers whose object of study is more specific and related to the informatic culture, such as, Computer Science, Computer Engineering, Information Systems, Information Technology and Software Engineering, called computational sciences (ACM 2005).

Consequently, it is hoped that the professionals who graduate from all these careers have appropriated the main scientific and technical advances related to informatic. In addition, in the case of the computationals sciences majors, they must have developed skills that allow them to design, write, debug and maintain the source code of computer programs; code that must be written in a specific language and often requires knowledge of various disciplines, specialized algorithms and formal logic; from which these professionals can create programs that exhibit the desired behavior (Salgado, Gorina & Alonso 2013). A valid strategy in this direction is to begin to teach programming using the algorithms as schematic resources through pseudocode as the main language, to represent the model of the resolution of a problem (Arellano et al. 2012; Blanco, Salgado & Alonso 2016).

Considering all of the above, this article aims to determine the shortcomings that are manifested in the teaching-learning process of the resolving computational programming problems and its dynamics of algorithmization in the majors of computational sciences of the University of Oriente, Cuba: Bachelor's degree in Computing Science, Engineering in Telecommunications and Electronics, Informatics Engineering and Automatic Engineering.

The teaching - learning process of resolving computational programming problems has been approached by numerous researchers, who have obtained important results in the search for a way to teach to program so that the student is able to create his own strategies consciously. Thus, authors such as Arellano et al. (2014) and Ma et al. (2011) assert that the fragility of knowledge in programming is due to the lack of a computer mental model that serves as the basis for creating viable algorithms. But although the conception of this model could be considered an alternative to favor the activity of programming, this is not enough to create efficient programs, since other mathematical, logical and computational knowledge must be incorporated, allowing an integrative perspective to address it.

On the other hand, the venezuelan researchers Torres and Torres (2016), have determined that when students solve problems of programming, they manifest lack of abstraction, few mathematical knowledge and deficiencies in the process of reading and interpretation of problems. In addition to this the student is generally focused on the language tool to be used, rather than in the domain of computational logic. …